Diffuse tissue damage from impact or blast traumatic brain injury (TBI), various illnesses, intoxication due to drugs or alcohol, sleep deprivation, and the like degrade information processing by the brain, often resulting in impairments in sensorimotor function. Deficits in dynamic visual processing and smooth-pursuit tracking can indicate that such an impairment exists. Indeed, eye movements are the most frequent, biomechanically-simplest, voluntary, visually-driven motor responses, providing a model system to assess the sequelae of brain insult, injury, and impairment. For more than a century, neurologists, psychologists, and psychiatrists have recognized that oculomotor behavior can reflect functional consequences of neural pathology, resulting in an extensive catalogue of qualitative oculomotor signs of drug toxicity, brain injury, and neurological disease, as well as standard ranges for normal behavior on common tasks.
Thus, oculomotor exams are used in both clinical (e.g., localizing lesions, diagnosing vestibular disorders, and detecting cranial nerve palsies) and field (e.g., detecting alcohol intoxication and fatigue) settings. Following TBI, oculomotor signs, such as disconjugate gaze, impaired saccadic inhibition, increased movement latency, amplified directional error, and impaired predictive tracking, have been reported, all consistent with impaired visual processing. However, the need for a readily-available clinical tool to quantitatively and systematically assess motion processing persists. To this end, leaders in the oculomotor field have proposed using oculomotor metrics as biomarkers of disease or trauma.
Current oculometric approaches do not convert qualitative patterns of multi-dimensional deficits (e.g., prolonged latencies, sluggish accelerations, reduced gain, elevated direction noise, etc.) expressed in the raw native units of the measurements (e.g., ms, deg/s2, etc.) into standardized normal units that can be used to make meaningful comparisons of the severity of deficits across these disparate dimensions (and associated disparate units), as well as to combine these multiple individual deficits into a single scalar measure of overall impairment specific to a particular potential disease or injury state. Accordingly, an improved approach to the processing of multi-variate oculomotor data used to detect and characterize sensorimotor impairment may be beneficial.